As enterprises accelerate their migration from traditional circuit switched telephony services to Internet Protocol (IP) Telephony solutions, a major consideration is their ongoing concern as to the potential reliability of the proposed IP voice services versus that of their current infrastructure. Indeed, in many call center environments, the potential cost of downtime is often greater than the implied benefits of migrating to IP Telephony. As such, it is often crucial for an enterprise system to meet a certain level of availability (e.g., 99.99% available) for the entire enterprise system or for at least one or more site(s) or subsystem(s) of the system.
The availability of a switching system is traditionally defined as the probability that the system is operational (i.e., percentage of uptime). The availability is generally calculated from an end-user's perspective and does not necessarily reflect the frequency of individual component failures or required maintenance where they do not affect the availability of the overall system to an end-user. The telecommunications industry requires a high degree of rigor, structure and methodologies for determining whether a device or service is operational. The switching system, including both hardware and software, and the supporting data network transport layer can be designed with back-up servers and alternate traffic routes in order to assure high level of availability.
The Alternative Methodology in Assessing Network Availability discussed here will assess the transport layer network availability when designed with back-up servers and alternate traffic routes. A by-product of this methodology is providing the ability to determine the degree of improvement in system availability, in quantitative terms, obtained through the use of back-up servers and/or alternative traffic routing. Moreover, the methodology must be applicable to configurations in which the various traffic route failure rates are arbitrary (i.e., not necessarily all equal.)
There are currently two methodologies for obtaining these calculations. The first methodology involves using purely mathematical models. More particularly, one common approach is by means of the combinetorics method, which entails solving for the coefficients of Network Reliability Polynomials. This combinetorics method involves the evaluation of network availability by accounting for all possible routes, including the alternative routes, between the nodes (e.g., remote locations) in a network configuration. However, solving for the network availability using the combinetorics method becomes exponentially complex as the number of nodes in the network increases. When a network comprises more than about six nodes (e.g., remote locations in the network configuration), the corresponding combinatorial mathematics become intractable, thus making it almost impossible to find a closed-form solution for the network availability. Rather than being able to solve for the actual network availability in such complex networks, the combinetorics method is only able to provide upper and lower bounds between which the network availability is guaranteed to fall. The combinetorics method can, therefore, only offer an estimation of the overall network availability. Moreover, to solve for the coefficients of Network Reliability Polynomials, most existing combinatorial approaches rely upon the simplifying assumption that all links between the nodes have equal failure rates. However, such an assumption is quite unrealistic for actual configurations in the field, thus resulting in misleading estimations of network availability.
The second methodology is described in U.S. patent application Ser. No. 11/087,200, entitled “Traffic Based Availability Analysis”, the entire contents of which are hereby incorporated herein by this reference in its entirety. The methodology described in that patent application utilizes non-stochastic simulation (“bulk traffic flow”). The methodology described therein eliminates the necessity to assume that all links between the network nodes have equal failure rates. The methodology of that application, however, does not include a way to account for backup servers and/or alternate traffic routing.
It would therefore be desirable to have a methodology which will provide accurate network availability values (as opposed to lower bounds and upper bounds) while accounting for back up servers and/or alternative traffic routing in the system design. Moreover, it will also apply to networks with arbitrary component failure rates (i.e., without relying on the assumption that all links have the same failure rate).